数据库审计
- 作者仓库星标 39
- 作者更新于 实时读取
- 作者仓库 awesome-omni-skill
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 92 / 100 · 已通过审计
- 作者 / 版本 / 许可
- @diegosouzapw · v1.0 · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- 未声明(默认跨平台)
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- Shell 执行
- 允许写入 / 修改
- 网络行为
- 仅限本地
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: consensus-voting
description: Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflic…
category: AI 智能
runtime: 无特殊运行时
---
# consensus-voting 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、执行终端命令、写入/修改文件、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、执行终端命令、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、执行终端命令、写入/修改文件。
先用一个小任务确认它会围绕“Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: consensus-voting
description: Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflic…
category: AI 智能
source: diegosouzapw/awesome-omni-skill
---
# consensus-voting
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection」组织步骤,不把推断写成作者事实。
- 读取文件、执行终端命令、写入/修改文件;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "consensus-voting" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Step 1: Define Voting Parameters / Step 2: Collect Votes / Vote Collection
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、执行终端命令、写入/修改文件 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Consensus Voting Skill
Step 1: Define Voting Parameters
Set up the voting session:
voting_session:
topic: 'Which database to use for the new service'
options:
- PostgreSQL
- MongoDB
- DynamoDB
quorum: 3 # Minimum votes required
threshold: 0.6 # 60% agreement needed
weights:
database-architect: 2.0 # Expert gets 2x weight
security-architect: 1.0
devops: 1.5
Step 2: Collect Votes
Gather agent recommendations:
## Vote Collection
### database-architect (weight: 2.0)
- Vote: PostgreSQL
- Rationale: Strong ACID guarantees, mature ecosystem
- Confidence: 0.9
### security-architect (weight: 1.0)
- Vote: PostgreSQL
- Rationale: Better encryption at rest, audit logging
- Confidence: 0.8
### devops (weight: 1.5)
- Vote: DynamoDB
- Rationale: Managed service, auto-scaling
- Confidence: 0.7
Step 3: Calculate Consensus
Apply weighted voting:
PostgreSQL: (2.0 * 0.9) + (1.0 * 0.8) = 2.6
DynamoDB: (1.5 * 0.7) = 1.05
MongoDB: 0
Total weight: 4.5
PostgreSQL: 2.6 / 4.5 = 57.8%
DynamoDB: 1.05 / 4.5 = 23.3%
Threshold: 60% → No clear consensus
Step 4: Resolve Conflicts
When no consensus is reached:
Strategy 1: Expert Override
- If domain expert has strong opinion (>0.8 confidence), defer to expert
Strategy 2: Discussion Round
- Ask dissenting agents to respond to majority arguments
- Re-vote after discussion
Strategy 3: Escalation
- Present options to user with pros/cons from each agent
- Let user make final decision
Step 5: Document Decision
Record the final decision:
## Decision Record
### Topic
Which database to use for the new service
### Decision
PostgreSQL
### Voting Summary
- PostgreSQL: 57.8% (2 votes)
- DynamoDB: 23.3% (1 vote)
- Consensus: NOT REACHED (below 60% threshold)
### Resolution Method
Expert override - database-architect (domain expert)
had 0.9 confidence in PostgreSQL
### Dissenting Opinion
DevOps preferred DynamoDB for operational simplicity.
Mitigation: Will use managed PostgreSQL (RDS) to
reduce operational burden.
### Decision Date
2026-01-23
- Quorum Required: Don't decide without minimum participation
- Weight by Expertise: Domain experts get more influence
- Document Dissent: Record minority opinions for future reference
- Clear Thresholds: Define what constitutes consensus upfront
- Escalation Path: Have a process for unresolved conflicts
The architect wants microservices but the developer prefers monolith.
Resolve this conflict.
Voting Process:
## Voting: Architecture Style
### Votes
- architect: Microservices (weight 1.5, confidence 0.8)
- developer: Monolith (weight 1.0, confidence 0.9)
- devops: Microservices (weight 1.0, confidence 0.6)
### Calculation
Microservices: (1.5 _ 0.8) + (1.0 _ 0.6) = 1.8
Monolith: (1.0 \* 0.9) = 0.9
Microservices: 66.7% → CONSENSUS REACHED
### Decision
Microservices, with modular monolith as migration path
### Dissent Mitigation
Start with modular monolith, extract services incrementally
to address developer's maintainability concerns.
Rules
- Always require quorum before deciding
- Weight votes by domain expertise
- Document dissenting opinions for future reference
Related Workflow
This skill has a corresponding workflow for complex multi-agent scenarios:
- Workflow:
.claude/workflows/consensus-voting-skill-workflow.md - When to use workflow: For critical multi-agent decisions requiring Byzantine fault-tolerant consensus with Queen/Worker topology (architectural decisions, security reviews, technology selection)
- When to use skill directly: For simple voting scenarios or when integrating consensus into other workflows
Workflow Integration
This skill enables decision-making in multi-agent orchestration:
Router Decision: .claude/workflows/core/router-decision.md
- Router spawns multiple reviewers, then uses consensus to resolve conflicts
- Planning Orchestration Matrix triggers consensus voting for review phases
Artifact Lifecycle: .claude/workflows/core/skill-lifecycle.md
- Consensus voting determines artifact deprecation decisions
- Multiple maintainers vote on breaking changes
Related Workflows:
swarm-coordinationskill for parallel agent spawning before voting- Enterprise workflows use consensus for design reviews
- Security reviews in
.claude/workflows/enterprise/require security-architect consensus
Memory Protocol (MANDATORY)
Before starting:
cat .claude/context/memory/learnings.md
After completing:
- New pattern ->
.claude/context/memory/learnings.md - Issue found ->
.claude/context/memory/issues.md - Decision made ->
.claude/context/memory/decisions.md
ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核